A Logical Model for Predicting Minority Representation: Application to Redistricting and Voting Rights Cases

Abstract

Understanding when and why minority candidates emerge and win in particular districts entails critical implications for redistricting and the Voting Rights Act. I introduce a quantitatively predictive logical model of minority candidate emergence and electoral success—a mathematical formula based on deductive logic that can logically explain and accurately predict the exact probability at which minority candidates run for office and win in given districts. I show that the logical model can predict about 90% of minority candidate emergence and 95% of electoral success by leveraging unique data of mayoral elections in Louisiana from 1986 to 2016 and state legislative general elections in 36 states in 2012 and 2014. I demonstrate that the logical model can be used to answer many important questions about minority representation in redistricting and voting rights cases. All applications of the model can be easily implemented via an open-source software logical.

Rising Tides or Political Ripcurrents? Gentrification and Minority Representation in 166 Cities

“…Several studies have explored the relationship between local racial and ethnic composition and the diversity of candidates who run for o ce, finding that it is one of the strongest predictors of whether minority candidates run for o ce and are ultimately successful (Canon et al 1996;Juenke 2014;Shah 2014;Fraga 2016); gentrification signals a reversal of this phenomenon. Supporting this intuition, the pro-minority margin in the previous election and the proportion of minority residents in a community are key predictors of whether minority candidates run for o ce in a given election and win (Atsusaka 2021). If gentrification alters the local composition of a community, fewer minority candidates should be seen in political o ces.…”

“…Supporting this intuition, the pro-minority margin in the previous election and the proportion of minority residents in a community are key predictors of whether minority candidates run for office in a given election and win (Atsusaka 2021). If gentrification alters the local composition of a community, fewer minority candidates should be seen in political offices.…”

The Geography of Racially Polarized Voting: Calibrating Surveys at the District Level

“…We use the term cohesion to refer to the voting behavior of a group (Atsusaka 2021; Pildes 2002). Cohesion equals the absolute deviation of the point estimate of the percentage of a group that votes for the Republican from 50%.…”

“…Finally, we turn to the potential of groups to form coalitions. The emerging voting power of Black and Hispanic groups over the past three decades and the cohesiveness of these groups raises the possibility that the two groups may vote sufficiently strongly together in general elections to be able jointly to elect their preferred candidates (Atsusaka 2021; Axelrod 1972; Barreto, Collingwood, and Manzano 2010; Grofman, Handley, and Lublin 2001). The demographic realities of contemporary America are putting pressure on voting rights law to accommodate the possibility of multiracial coalitions (Pildes 2002).…”

Districting Without Parties: How City Council Maps Increase Minority Representation

“…Because our conclusions about Latino electoral success under alternative districting schemes rely on predictions generated by this model, its validity and predictive power are of the utmost importance for our findings to hold water. Fortunately, a sizeable literature has been devoted to the problem of predicting minority descriptive representation using district characteristics, with notable recent developments by Atsusaka (2021) and Fraga, Gonzalez Juenke and Shah (2020). After testing a variety of approaches, we select a relatively parsimonious logistic regression specification that performs well out of sample, correctly classifying 81% of the cases.…”